Scene-aware synthetic human motion generation using neural networks

Abstract

A motion diffusion model may be pre-trained on motion data, and a scene-aware component (e.g., one or more layers of a neural network) may be connected and used to extract and inject a representation of scene information into the pre-trained motion diffusion model. For example, to predict orientations of joint waypoints along a path through a particular 3D scene, a scene-aware input channel that accepts a representation of the 3D structure of the scene may be added to a pre-trained motion diffusion model. To predict orientations of joint waypoints along a path that interacts with a 3D object in the 3D scene, a scene-aware input channel that accepts a representation of the 3D object and/or a surface thereof may be added to a pre-trained motion diffusion model. As such, the resulting scene-aware motion diffusion model(s) may be tuned on motion-scene data and used to generate human motion.